Long-duration correlation and attractor topology of the heartbeat rate differ for healthy patients and those with heart failure

The point process formed by the sequence of human heartbeats exhibits long-duration power- law correlation. We obtain the normalized coincidence rate g(2)((tau) ) of the underlying point process and demonstrate that the correlation is stronger for patients with normal hearts than those with heart failure. This is consistent with the greater rate fluctuations observed in the normal heart. A number of statistical measures are used to establish the existence and reveal the form of the correlation, including rescaled range analysis, pulse- number distribution, Fano-factor time curve (FFC), and power spectral density. The normalized coincidence rate is obtained from the FFC. The long-duration, power-law correlation observed in the sequence of heartbeats is similar to that observed at a number of neurophysiological loci in a variety of species. We also obtain the box-counting estimate of the attractor's fractal dimension from a phase-space reconstruction and analysis of the trajectory of the number of heartbeat events. This approach reveals that the heartbeats of normal patients exhibit an attractor of higher dimension than those of heart-failure patients.